{"id":"https://openalex.org/W7169776224","doi":"https://doi.org/10.48550/arxiv.2607.15400","title":"Unsupervised Keypoints for Real-Time Fall Detection: Comparative Analysis Under Real-world Conditions with Predictive Bandwidth Reduction","display_name":"Unsupervised Keypoints for Real-Time Fall Detection: Comparative Analysis Under Real-world Conditions with Predictive Bandwidth Reduction","publication_year":2026,"publication_date":"2026-07-16","ids":{"openalex":"https://openalex.org/W7169776224","doi":"https://doi.org/10.48550/arxiv.2607.15400"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.15400","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15400","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.15400","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109693432","display_name":"Tasmiah Haque","orcid":"https://orcid.org/0009-0004-8486-2018"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haque, Tasmiah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141168308","display_name":"Jacob Kosinski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kosinski, Jacob","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090786551","display_name":"Sumit Mohan","orcid":"https://orcid.org/0000-0001-9642-1923"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohan, Sumit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141173514","display_name":"Mohammad Abdullah Al-Mamun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Al-Mamun, Mohammad Abdullah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5005981376","display_name":"S R Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Srinjoy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.5613999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.5613999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.22660000622272491,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.120899997651577,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.588100016117096},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5078999996185303},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.4438999891281128},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.44269999861717224},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4406999945640564},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.4318000078201294},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.38609999418258667}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.785099983215332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6452000141143799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.588100016117096},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47290000319480896},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.4438999891281128},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.44269999861717224},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4406999945640564},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.38609999418258667},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.2989000082015991},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2653999924659729},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.15400","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15400","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.15400","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.15400","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Falls":[0],"among":[1],"older":[2],"adults":[3],"are":[4,142,147],"a":[5,47,127],"major":[6],"safety":[7],"challenge,":[8],"but":[9,37,131],"continuous":[10],"monitoring":[11],"is":[12,24,34,239],"difficult":[13],"to":[14,39,150,191,193],"sustain.":[15],"Video":[16],"captures":[17],"fall-related":[18],"posture":[19],"and":[20,29,41,62,70,76,84,96,103,152,181,229],"motion,":[21],"yet":[22],"deployment":[23],"limited":[25],"by":[26,134],"privacy,":[27],"computation,":[28],"bandwidth.":[30],"Supervised":[31],"pose":[32],"estimation":[33],"anatomically":[35],"interpretable":[36],"vulnerable":[38],"occlusion":[40,151],"partial":[42,153],"body":[43,195,237],"visibility.":[44],"We":[45,87],"propose":[46],"privacy-preserving":[48],"framework":[49,90],"that":[50,114,221,230],"replaces":[51],"RGB":[52],"transmission":[53],"with":[54],"compact":[55],"motion":[56],"representations":[57],"based":[58],"on":[59,91,200],"unsupervised":[60,145,176,231],"keypoints":[61,125,146,168,177,232],"predictive":[63],"temporal":[64,216],"modeling.":[65],"Local":[66],"processing":[67],"performs":[68],"segmentation":[69],"keypoint":[71],"extraction;":[72],"variational":[73],"recurrent":[74],"prediction":[75],"sequence":[77],"classification":[78],"then":[79],"detect":[80],"falls":[81],"from":[82],"observed":[83],"forecasted":[85],"motion.":[86],"evaluate":[88],"the":[89,92,215],"UR":[93],"Fall":[94,98],"Detection":[95],"Human":[97],"datasets":[99],"using":[100],"random,":[101],"subject-disjoint,":[102],"occlusion-based":[104,165],"splits.":[105],"Under":[106,121,164],"random":[107],"splits,":[108],"neither":[109],"representation":[110,222],"consistently":[111],"dominates,":[112],"suggesting":[113],"standard":[115],"protocols":[116],"may":[117],"hide":[118],"meaningful":[119],"differences.":[120],"subject-disjoint":[122],"evaluation,":[123,166],"supervised":[124,167,210],"show":[126,220],"statistically":[128],"significant":[129],"advantage,":[130],"performance":[132],"varies":[133],"subject:":[135],"they":[136,156],"perform":[137],"better":[138],"when":[139,236],"anatomical":[140,186],"landmarks":[141],"visible,":[143],"whereas":[144],"more":[148,158],"robust":[149],"visibility,":[154],"though":[155],"produce":[157],"false":[159],"positives":[160],"for":[161],"complex":[162],"activities.":[163],"miss":[169],"nearly":[170],"half":[171],"of":[172],"all":[173],"falls,":[174],"while":[175],"retain":[178],"strong":[179],"sensitivity":[180],"substantially":[182],"outperform":[183],"them.":[184],"Their":[185],"independence":[187],"allows":[188],"spatial":[189],"anchors":[190],"adapt":[192],"visible":[194],"structure":[196],"rather":[197],"than":[198],"fail":[199],"absent":[201],"landmarks.":[202],"The":[203],"gap":[204],"widens":[205],"under":[206],"bandwidth":[207],"constraints,":[208],"where":[209],"localization":[211],"errors":[212],"compound":[213],"through":[214],"model.":[217],"These":[218],"findings":[219],"choice":[223],"should":[224],"reflect":[225],"expected":[226],"visual":[227],"conditions":[228],"offer":[233],"an":[234],"advantage":[235],"visibility":[238],"compromised.":[240]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-21T00:00:00"}
